From Books to Real Life
Faculty Mentor Name
Rubaiya Murshed
Format Preference
Poster
Abstract
This project examines how narrative-based pedagogy influences student learning and how Artificial Intelligence (AI) can help create effective story-driven homework questions that connect abstract formulas to real-world contexts.
Homework is a cornerstone of education, providing opportunities for practice and a deeper understanding of concepts. Traditionally, homework assignments are criticized for lacking relevance to real-world experiences, which can limit motivation and the perceived value of academic work. This is particularly the case for courses that do not include laboratory activities. Recent innovations in educational practices emphasize narrative-rich, contextually meaningful assignments that bridge classroom learning with real-life applications, triggering both emotional and cognitive engagement. The advent of AI offers a new way to generate diverse, realistic, and personalized experiences for both teachers and students.
Preliminary survey results indicate that most students felt narrative-based assignments enhanced real-world relevance and the importance of course content, and they expressed strong support for this approach. However, they recommended shorter versions to reduce reading time and make it easier to identify key data for problem-solving.
Future work will focus on designing effective AI-generated narratives and identifying AI’s limitations by systematically varying narrative length and technical depth to examine student perceptions, determining whether perceived benefits translate into measurable learning gains, and exploring workflows in which students co-create or revise AI-generated narratives to study impacts on conceptual understanding and attitudes toward AI in engineering education.
From Books to Real Life
This project examines how narrative-based pedagogy influences student learning and how Artificial Intelligence (AI) can help create effective story-driven homework questions that connect abstract formulas to real-world contexts.
Homework is a cornerstone of education, providing opportunities for practice and a deeper understanding of concepts. Traditionally, homework assignments are criticized for lacking relevance to real-world experiences, which can limit motivation and the perceived value of academic work. This is particularly the case for courses that do not include laboratory activities. Recent innovations in educational practices emphasize narrative-rich, contextually meaningful assignments that bridge classroom learning with real-life applications, triggering both emotional and cognitive engagement. The advent of AI offers a new way to generate diverse, realistic, and personalized experiences for both teachers and students.
Preliminary survey results indicate that most students felt narrative-based assignments enhanced real-world relevance and the importance of course content, and they expressed strong support for this approach. However, they recommended shorter versions to reduce reading time and make it easier to identify key data for problem-solving.
Future work will focus on designing effective AI-generated narratives and identifying AI’s limitations by systematically varying narrative length and technical depth to examine student perceptions, determining whether perceived benefits translate into measurable learning gains, and exploring workflows in which students co-create or revise AI-generated narratives to study impacts on conceptual understanding and attitudes toward AI in engineering education.